Firstwrkshnotes » History » Revision 9
Revision 8 (Corinna Gries, 03/10/2014 02:08 PM) → Revision 9/20 (Corinna Gries, 03/10/2014 02:16 PM)
h1. Workshop Notes
are on etherpad: https://epad.nceas.ucsb.edu/p/commdyn-20140105
h1. Metrics brainstorming:
* what are you currently using
* what would you like to use
* how widely is it used
* can it be applied to different biological community datasets (sampling approach)
* is it already coded {in R}
h2. Metrics
# *Diversity* (all of these are generally in R, mostly in vegan)
## Jaccard index
## Simpson's diversity
## Shannons index
## Turnover - different ways to calculate
## Dominance
## Evenness
## Richness
## Rank abundance shift
## Proportion of overall diversity
## Beta diversity
# *Community metrics/ordination*
## NMDS (vegan)
## PCA (vegan)
## Bray curtis (vegan)
## Variance tracking, quantify variability change
## Position in ordination-space
# *Spatial*
## patch scale
## spatial autoregression
## Endemism
## Summary of species' positions within their ranges
## meta community statistics
# *Mechanistic models*
## MAR, needs driver matrix, problem auto-corelation, mostly fresh water or marine (Eli Holmes has state-space MAR in R implemented, not sure if it's on CRAN) http://cran.r-project.org/web/packages/MARSS/index.html
## MANOVA (vegan? Also, permanova is in vegan)
## Ecosystem function (e.g. N deposition)
## interaction population models - inter specific competition (Ben Bolker's book and corresponding package)
## Economically/legally relevant metrics (e.g. Maximum sustainable yield)
# *Food webs*
## connectance
## network analysis
# *Traits/phylogentic*
## functional/phylogenetic diversity
## species aggregation (functional groups, trophic levels
## phylogenetic dispersion (ape etc. -- this stuff is all in R)
## Native/exotic
## Phylogeographic history
# *Temporal indices*
## species turnover
## rate of return
## Variance ratio
## Mean-variance scaling
## Spectral analysis
## Regresssion windows (strucchange)
## time series models of abundance -- metric would be parameters of model
# *null models*
# *Comparative analysis of small noise vs large noise systems. What drives differences?*
h2. Issues:
#length of time series relative to lifespan of organisms
>
WMI toolbox
#high frequency data needed
>
sample too frequently then don't see signal, sample to far about miss all dynamics
#type of variable being measured
>
abundance, biomass, production
#
Rare species as background noise
rank abundance curves back again
Comparative analysis of small noise vs large noise systems. What drives differences?
h2. Coded in R
* Richness/diversity metrics: http://cran.r-project.org/web/packages/vegan/index.html
* Diversity metrics (alpha, beta, gamma): http://cran.r-project.org/web/packages/vegetarian/index.html
* Hubble metrics: http://cran.r-project.org/web/packages/untb/index.html
* Leading indicators, variance, autocorrelation, skew, heteroscedasticity: http://cran.at.r-project.org/web/packages/earlywarnings/index.html
not yet coded:
* state-space models and community level resilience